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Graph-Based Method for Fault Detection in the Iron-Making Process
An RQ(安汝峤)1; Yang CJ(杨春节)1; Pan YJ(潘怡君)2,3,4
Department数字工厂研究室
Source PublicationIEEE Access
ISSN2169-3536
2020
Volume8Pages:40171-40179
Indexed BySCI ; EI
EI Accession number20201208308976
WOS IDWOS:000525550300022
Contribution Rank2
Funding OrganizationNational Natural Science Foundation of China under Grant 61933015
KeywordFault detection graph iron-making process Mahalanobis distance minimum spanning tree
Abstract

Since the iron-making process is performed in complicated environments and controlled by operators, observation labeling is difficult and time-consuming. Therefore, unsupervised fault detection methods are a promising research topic. Recently, an unsupervised graph-based change point detection method has been introduced, and the graph of observations is constructed by the minimum spanning tree. In this paper, a novel fault detection method based on the graph for an iron-making process is proposed, and a weight calculation method for constructing the minimum spanning tree is introduced. The Euclidean distance and Mahalanobis distance are combined to calculate the weights in the minimum spanning tree, which contain important relations of variables. The distance calculation method is determined by the correlation coefficients of variables. Each testing observation is set as a change point candidate, and a change point candidate divides the observations into two groups. The number of a special type of edge in the minimum spanning tree is used as a fault detection statistic. That special edge connects two observations from two different groups. The minimum number of that type of edge corresponding to the change point candidate is a true change point. Finally, numerical simulation is used to test the power of the proposed method, and a real iron-making process including low stock, cooling, and slip faults is implemented to illustrate the effectiveness of fault detection in industrial processes.

Language英语
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS KeywordPRINCIPAL COMPONENT PURSUIT ; MAHALANOBIS DISTANCE
WOS Research AreaComputer Science ; Engineering ; Telecommunications
Funding ProjectNational Natural Science Foundation of China[61933015]
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/26566
Collection数字工厂研究室
Corresponding AuthorYang CJ(杨春节)
Affiliation1.Department of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
2.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China
3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
Recommended Citation
GB/T 7714
An RQ,Yang CJ,Pan YJ. Graph-Based Method for Fault Detection in the Iron-Making Process[J]. IEEE Access,2020,8:40171-40179.
APA An RQ,Yang CJ,&Pan YJ.(2020).Graph-Based Method for Fault Detection in the Iron-Making Process.IEEE Access,8,40171-40179.
MLA An RQ,et al."Graph-Based Method for Fault Detection in the Iron-Making Process".IEEE Access 8(2020):40171-40179.
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